Revision as of 17:19, 15 February 2018

Deliverable D1.2 - Data Management Plan

Introduction

As part of the Pilot Action on Open Access to Research Data in Horizon 2020, participants in PrimeFish will have to create a Data Management Plan (DMP). The Data Management Plans included in this document outlines the general information regarding each data set, covering several subjects all relevant to data management and the possible reuse of data sets. Each data management plan (DMP) gives an overview on what sort of data the data set contains, and what (if any) standards are being used. Information about the content of the data set includes both an overview of the different variables included as well as metadata. This goes for both data extracted from existing sources as well as data developed over the course of the PrimeFish-project.

A major focal point of the Pilot Action on Open Access to Research Data is the possibility of sharing and reusing data sets. Each DMP outlines whether or not access to the data is (semi-)restricted to certain institutions or if it is available without restrictions. In any case, the DMP describes who has the right to use to it, and how it might be accessed. This includes access procedures, which repository the data is stored in, etc. It also details possible barriers to dissemination such as the need for certain software, language barriers, etc.

As the possibilities of reusing and sharing data depends on, among other things, the methods used for preserving and archiving the data sets, procedures for long-term storage of data are also outlined. This section details for how long the data set will be preserved (for a given time period or indefinite), methods of backup, the possibility of future incongruence between the extracted data and the original sources due to periodical updates of the latter one, etc.

All submitted data management plans are included in the appendix of this document. They are grouped according to the corresponding work package (WP). The data management plans within are listed first according to sub-task where this has been provided. If no task-number has been listed, they have been placed in no particular order. Where possible, the corresponding WP- and task-number is listed for each DMP along with the institution. In cases where two or more identical data management plans were submitted for different tasks, these have been included as only one form.

Methods

A DMP-template was distributed among all project participants, along with instructions on how to fill out the form. Instructions were given both by e-mail and through a separate, and more detailed, "explanation-file" (both the template and explanation are included in the appendix). The information requested in the DMP-template was meant to form the basis for deliverables 1.1 and 1.2 ("Guidelines on data collection methods", and the "Data Management Plan", respectively). A draft of the deliverable containing all submitted forms was sent out to the project participants in order to be reviewed. The deliverable was later edited based on the feedback provided by the participants.

Conclusion

The Data Managements Plans provided in this document give a detailed overview on the essential elements in the corresponding data sets. They have been reworked based on feedback provided by the project participants. However, the process has highlighted some slight difficulties concerning both the level of detail provided and the potential for harmonization between DMPs. Different data sets corresponds to different WPs, all of whom have different schedules. As a result, the amount of information regarding the data sets might vary greatly depending on how far along in the process each participant is at any given time. It also appears that the project participants have interpreted the DMP requirements differently, leading to different ways of filling out the form. This is turn has made harmonizing between DMPs difficult.

Acknowledgements

We wish to thank all the project participants who have contributed to the completion of this deliverable.

References

Guidelines on Data Management in Horizon 2020. Version 1, Dec. 11. 2013.
Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020. Version 2.0, Oct. 30th. 2015.

Appendix

WP2

Data set reference and name	Herring – Questionnaire on productivity development and growth potential
WP/Task/Partner	WP2 – Task 2.1 – TTZ Bremerhaven
Data set description	Data set consists of qualitative results from questioning experts in the field of trading or producing herring on elements that may shape productivity development and the potential for growth.
Standards and metadata	Metadata (e.g. gender, size of company or country) will be described on an extra sheet within an excel file e.g. In case of using SPSS for storing and handling the data, metadata are directly entered into the SPSS-file as labels. Data contains both numbers and text/string variables. The preliminary dataset-structure is rows=interviewees, and columns= variables/questions. Transcripted data/personal data and coded/anonymized data are stored in separate files.
Data sharing	Data is stored at TTZ on a server that is only accessible for employees of TTZ. The data is saved in different formats: .xls (Microsoft Excel), .txt, .sav (SPSS 22). Data can be shared if necessary, provided all personal information from the interviewees is anonymized and if they have agreed to share data under these conditions. It can be sent by e-mail.
Archiving and preservation	All data at TTZ is saved and stored on a central server. The server is mirrored several times a week. If not deleted by coincidence, the data will be available as long as necessary.

Data set reference and name	Herring – Case study data on economic performance 2000-2012
WP/Task/Partner	WP2 – Task 2.1.2 Aalborg University
Data set description	Economic performance and prices Two data set will be used to assess the economic performance at sector level: The vessel and segment economic data from statistics Denmark: Full economic key indicators as average data for the vessels in the segment Stock levels (status) from ICES stock assessments. Development in the SSB of the main stock of herring and mackerel fished by the segment.
Standards and metadata	Data are stored in Excel. Purpose of data will be recorded. Time and date of creation will be recorded. Creator and author will be recorded. Location of creation will be recorded. Metadata at Statistics Denmark (www.dst.dk) and Ministry of Environment and Food, The Danish AgriFish agency (www.naturerhverv.dk/fiskeri/fiskeristatistik/)
Data sharing	i Raw data is publically available from original source. Processed data will be shared to partners through the project’s homepage. Data will be downloadable in Excel format in English.
Archiving and preservation	Raw data is archived and preserved with original source. Processed data is archived and preserved at the AAU server, which is mirrored on a daily basis and will be kept in the project period and longer according to PrimeFish agreements

Data set reference and name	Several sectors – Price and sale information on the European seafood market, 2000-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set contains weekly/monthly information on first sale, wholesale, import and retail prices and yearly info on consumption, landings, import/export, processing and aquaculture. The data is collected from EUMOFA (European Market Observatory for Fisheries and Aquaculture products).
Standards and metadata	Metadata is available at http://www.eumofa.eu/ (to be renewed in Dec.2015/Jan. 2016) Period: 2000 – up to data (will vary)
Data sharing	The EUMOFA data is publically available with 7 pre-defined queries for weekly data and tool for extracting data (ad-hoc) 16 pre-defined queries for monthly data and tool for extracting data (ad-hoc) 11 pre-defined queries for yearly data and tool for extracting data (ad-hoc)
Archiving and preservation	EUMOFA server maintained and updated by the EUMOFA consortium

Data set reference and name	Groundfish/cod – Price and volume information, 2006-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set contains data on volumes (catch/landing, supply/market) and price developments for groundfish/cod in different whitefish markets. The data is gathered by Kontali.
Standards and metadata	Groundfish Weekly Update Kontali Monthly Cod Report Data is saved in Excel-format Publications are in pdf-format (subscription) Period: 2006 – up to data
Data sharing	*In-house data may be available for non-commercial use upon request.
Archiving and preservation	Data is archived and preserved with original source. Data compiled for Kontali purpose is stored on an in-house server

Data set reference and name	Pelagic – Price, volumes and industry structure, 2000-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set contains various information on herring, mackerel and capelin. It includes quotes, catches/landings, export prices and –volumes, import, stock, as well as figures on fish meal and –oil production and export. The data stems from various countries. It is collected by Kontali.
Standards and metadata	Kontali Pelagic Weekly Update Kontali Monthly Pelagic report Pelagic world Period: 2000 – up to data Data is saved in Excel-format Publications in pdf-format (subscription)
Data sharing	*In-house data may be available for non-commercial use upon request.
Archiving and preservation	Data is archived and preserved with original source. Data compiled for Kontali purpose is stored on an in-house server

Data set reference and name	Salmon – Price, volume and company business statistics, 1994-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set contains data on prices, volumes and company statistics for salmonid production world-wide with focus on major production nations. The data is collected by Kontali.
Standards and metadata	KAB – Kontali Aquaculture Bulletin KAB – Weekly update Salmon Market Analysis Salmon World Period: 1994 – up to data (expanded over the period) Data is saved in Excel-format Publications in pdf-format (subscription)
Data sharing	In-house data may be available for non-commercial use upon request.
Archiving and preservation	Stored on an in-house server

Data set reference and name	Salmon – Norway – Economic and financial figures, 1996-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set consist of key financial figures (quantity, EBIT/EBT, cost figures, etc.) for the Norwegian salmon farming industry, including smolt producers, slaughterhouses and exporters. The data is collected by Kontali.
Standards and metadata	Salmon Farming Industry in Norway Period: 1996 – up to data (expanded over the period) Excel-format Publications in pdf-format (subscription)
Data sharing	*In-house data may be available for non-commercial use upon request.
Archiving and preservation	*Stored on an in-house server

Data set reference and name	Seabass, seabream – Price, volume, estimated juvenile figures and fish feed volumes, 2006-to date
WP/Task/Partner	WP2 – Kontali
Data set description	The data set contains key figures such as prices and volumes for export and sale, production estimates, fish feed information and economic performance data. The information is gathered by Kontali, and extracted from EuroStat and TurkStat.
Standards and metadata	Kontali Seabass & Seabream Monthly Report Period: 2006 – to date Data is saved in Excel-format Publications in pdf-format (subscription)
Data sharing	*In-house data may be available for non-commercial use upon request. Data collected as part of the PrimeFish project will be made available anonymized.
Archiving and preservation	Stored on an in-house server

Data set reference and name	Trout – Price, volume and company performance data
WP/Task/Partner	WP2 – Kontali
Data set description	The data set will contain volume and price information for harvest/production, export/import and retail/wholesale of (portion) trout. The data is on the main producing countries within the EU and Turkey. The data will be collected by Kontali.
Standards and metadata	*Data will be stored in Excel. Purpose of data will be recorded. Time and date of creation will be recorded. Creator and author will be recorded. Location of creation will be recorded. Appropriate scientific standards will be applied. Metadata will need to be developed following data being collected.
Data sharing	*Data is publically available from the different original sources Data will be shared through the project’s web-page Data will be downloadable in Excel format. Data is described in English in Excel file and is available in English at original sources.
Archiving and preservation	*Original data will be archived and preserved with the different original sources Data collected for the purpose of PrimeFish will be made available to the PrimeFish consortium through the PrimeFish web site, and for outside interest upon request. Kontali might choose to maintain and preserve the data beyond the lifetime of PrimeFish, if so, the data will be in-house and will be available for non-commercial use upon request.

Data set reference and name	Salmon – Canada – Economic performance and prices
WP/Task/Partner	WP2 – MemU
Data set description	The data set on economic performance and prices for Atlantic salmon will contain key data on production volumes and values, as well as product forms and export market info. The data is gathered from company websites, interviews/questionnaires, and various reports. Ref: Can1_21_AQ_SAL
Standards and metadata	*Data will be collected and compiled into an excel spreadsheet or other appropriate template which will be recorded and stored on an institutional restricted access repository Purpose of the data will be recorded Time and date of creation will be recorded Creator or author of the data will be recorded Location where the data was created will be identified Standards used will be identified Data sets will be identified using the following naming system: Identification code_FAO regional code_Type of fishery_Species common name_data type_Source_WP
Data sharing	*Data will be collected by MemU through its Marine Institute (MI). It will be stored on an institutional restricted access repository. Data will be made available to relevant work package leaders via MI’s Sharepoint restricted access website.
Archiving and preservation	*Data will be stored for a minimum time equal to the duration of the PrimeFish on the MI institutional repository for active projects. Upon project completion the data will be transferred to the institutional archive repository as per institutional policies and procedures. No additional resources will be required. The MI has in-house resources through its ICT department that are working with the MemU research team to ensure the system meets the requirements of PrimeFish. Data will be organized according to MI standard policies procedures and in compliance with the Institute’s ISO quality system.

Data set reference and name	Cod – Canada – Economic performance and prices
WP/Task/Partner	WP2 – MemU
Data set description	The data set will contain data on the economic performance and prices for Atlantic cod. This includes prices and volume data for the landings and production, as well as market data (product forms, prices and export markets). The data is gathered from company websites, interviews/questionnaires, public sector statistical data and various reports. Ref: Can2_21_FI_COD
Standards and metadata	*Data will be collected and compiled into an excel spreadsheet or other appropriate template which will be recorded and stored on an institutional restricted access repository Purpose of the data will be recorded Time and date of creation will be recorded Creator or author of the data will be recorded Location where the data was created will be identified Standards used will be identified Data sets will be identified using the following naming system: Identification code_FAO regional code_Type of fishery_Species common name_data type_Source_WP
Data sharing	*Data will be collected by MemU through its Marine Institute (MI) and stored on an institutional restricted access repository. Data will be made available to relevant work package leaders via MI’s Sharepoint restricted access website.
Archiving and preservation	*Data will be stored for a minimum time equal to the duration of the PrimeFish on the MI institutional repository for active projects. Upon project completion the data will be transferred to the institutional archive repository as per institutional policies and procedures. No additional resources will be required. The MI has in-house resources through its ICT department that are working with the MemU research team to ensure the system meets the requirements of PrimeFish. Data will be organized according to MI standard policies procedures and in compliance with the Institute’s ISO quality system.

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